Image guided surgeries, laparoscopic or endoscopic, also benefit from the 2D-3D image registration where imaging acquisition devices are associated with the surgical devices
Applicative fields of the invention include image guided adaptive radiotherapy planning and treatment, image-guided biopsy as breast under ultrasound guidance or prostate biopsies using MRI images and transrectal ultrasound (TRUS) achieve a higher detection of cancer. Another application domain is image-guided surgery, as laparoscopic or endoscopic, in particular neurosurgery which benefits from 2D-3D image fusion for evaluation of intracranial tumours and vascular pathologies.
In many medical imaging applications, it is particularly useful to achieve a registration/mapping between a two-dimensional image of a partial view of an object of interest that is captured during an operation, also called intra-operative capture, whereas a three-dimensional volume where the same object of interest is present partially or completely acquired at a pre-operative stage. It should be noted that the object of interest could exhibit shape changes during surgery (tissue shift, respiratory motion, cardiac heart beating). Such registration is useful to guide surgeons during operation through the mapping of visual observations at surgery to the 3D pre-operative high resolution annotated data.
A particular problem in medical applications is that tissue shift, as well as breathing and heart motion during surgery, cause elastic deformations of the organs and make the registration of a 2D image acquired during operation with a 3D volume previously computed a particularly challenging problem.
More generally, medical applications that can benefit from an elastic 2D to 3D registration, with possibly multi-modal acquired images, are application fields for the invention.
Several methods for achieving registrations between pre-operative 3D images and intra-operative 2D images are known, but they require either a learning stage or to pre-process input data. The quality of the final result is highly dependent on the learning stage.
Many known methods are either dedicated to specific organs (for example the ones requiring manual segmentation of the organ of interest that perform registration by segmentation) or could address the task for specific image modalities and therefore cannot be re-used in other applications.
An aim of the present invention is to provide a 2D-to-3D elastic/deformable registration/fusion method that overcomes the cited drawbacks.
To this end, the invention concerns, according to a first aspect, a method for elastic registration of a two-dimensional source digital image of an object of interest with a slice of a three dimensional target volume of the object of interest, the method comprising defining a Markov Random Field framework comprising at least one undirected pairwise graph superimposed on the two-dimensional image domain comprising at least a set of regular vertices and at least a set of edges, defining at least a grid of control points, each control point corresponding to a vertex of the set of vertices, and a neighborhood system of edges associated with vertices.